TensorFlow neural network

import tensorflow as tf


class TensorflowNeuralNetwork:
    def __init__(self):
        model = tf.keras.models.Sequential()
        self.model = model
        model.add(tf.keras.layers.Flatten())
        model.add(tf.keras.layers.Dense(128, activation=tf.nn.relu))
        model.add(tf.keras.layers.Dense(128, activation=tf.nn.relu))
        model.add(tf.keras.layers.Dense(10, activation=tf.nn.sigmoid))
        self.model.compile(optimizer="SGD", loss="mean_squared_error", metrics=["accuracy"])
        # self.model.compile(optimizer="adamax", loss="sparse_categorical_crossentropy", metrics=["accuracy"])

    def train(self, x_train, y_train):
        self.model.fit(x_train, y_train, epochs=10)

    def evaluate(self, x_test, y_test):
        validation_loss, validation_accuracy = self.model.evaluate(x_test, y_test)
        print("Loss: " + str(validation_loss))
        print("Accuracy: " + str(validation_accuracy))